!pip install geopandas hvplot panel2. Exploratory Plots [Map]
3.3 Map
Finally, we can make a map to see how the variables vary across US states
import geopandas as gpd
import hvplot.pandas
import panel as pn# Convert from wide to long data
us_rescaled_final_long = pd.melt(us_rescaled_final,
id_vars = ['STATEFP', 'STATENS', 'GEOIDFQ', 'GEOID', 'STUSPS', 'NAME_x', 'LSAD','ALAND', 'AWATER', 'geometry', 'NAME_y', 'GEO_ID'],
value_vars=['MedHHInc', 'EducTotal', 'EducBelowHighSch', 'EducHighSch', 'EducAssoc', 'EducBach', 'TotalPop', 'TotalPop16', 'LabForTotal', 'Unemployed', 'PopPovertyDetermined', 'PovertyPop', 'PctBach', 'PovertyRate', 'UnemploymentRate', 'LabForParticipationRate', 'netexport', 'REALGDP', 'life_expectancy', 'Labor_Productivity_2023', 'REALGDPpercapita']
)chart3 = us_rescaled_final_long.hvplot(
c="value",
dynamic=False,
width=1000,
height=1000,
geo=True,
cmap="viridis",
groupby="variable")chart3